Substellar and low-mass dwarf identification with near-infrared imaging space observatories

Abstract

Aims. We aim to evaluate the near-infrared colors of brown dwarfs as observed with four major infrared imaging space observatories: the Hubble Space Telescope (HST), the James Webb Space Telescope (JWST), the Euclid mission, and the WFIRST telescope. Methods. We used the SPLAT SPEX/ISPEX spectroscopic library to map out the colors of the M-, L-, and T-type dwarfs. We have identified which color-color combination is optimal for identifying broad type and which single color is optimal to then identify the subtype (e.g., T0-9). We evaluated each observatory separately as well as the narrow-field (HST and JWST) and wide-field (Euclid and WFIRST) combinations. Results. The Euclid filters perform poorly typing brown dwarfs and WFIRST performs only marginally better, despite a wider selection of filters. WFIRST's W146 and F062 combined with Euclid's Y-band discriminates somewhat better between broad brown dwarf categories. However, subtyping with any combination of Euclid and WFIRST observations remains uncertain due to the lack of medium or narrow-band filters. We argue that a medium band added to the WFIRST filter selection would greatly improve its ability to preselect brown dwarfs its imaging surveys. Conclusions. The HST filters used in high-redshift searches are close to optimal to identify broad stellar type. However, the addition of F127M to the commonly used broad filter sets would allow for unambiguous subtyping. An improvement over HST is one of two broad and medium filter combinations on JWST: pairing F140M with either F150W or F162M discriminates very well between subtypes.

Euclidpreparation

“…We assigned colours for each spectral type by measuring colours for suitable sources in the SpeX Prism Library (Burgasser 2014), and selecting the median value for each spectral type. Holwerda et al (2018) recently presented Euclid NIR colours for the MLT population. They took a different approach, by measuring colours for the standard stars in the library; however, these individual spectra do not extend sufficiently bluewards to measure optical colours.…”

Default Parallels: The Science Potential of JWST Parallel Observations during TSO Primary Observations

“…Similarly, a search for the lowest-mass substellar objects belonging to the Milky Way can benefit from observations such as the above default parallels. The randomized sampling of the Milky Way volume equally benefits constraints on the shape of the Milky Way (Pirzkal et al 2005(Pirzkal et al , 2009Ryan et al 2005Ryan et al , 2011Ryan et al , 2017Holwerda et al 2014Holwerda et al , 2018van Vledder et al 2016). The near-infrared observations of JWST are sensitive to Figure 1.…”

“…The randomized nature of the fields would allow for a first survey of Galactic disk and halo substellar objects, down to freefloating super-Jupiters (e.g., Ryan et al 2017;Deacon 2018). These parallel searches for low/substellar objects benefit from color information (Holwerda et al 2018), accurate astrometry, or grism information, but they derive their statistical power from the randomized fields.…”

Default Parallels: The Science Potential Of JWST Parallel Observations During TSO Primary Observations

“…Similarly, a search for the lowest-mass sub-stellar objects belonging to the Milky Way can benefit from observations such as the above default parallels. The randomized sampling of the Milky Way volume equally benefits constraints on the shape of the Milky Way (Ryan et al 2005(Ryan et al , 2011Pirzkal et al 2005Pirzkal et al , 2009Holwerda et al 2014;van Vledder et al 2016;Ryan et al 2017;Holwerda et al 2018). The near-infrared observations of JWST are sensitive to the lowest-mass objects (Y-dwarfs) throughout the width of the Galactic disk and halo.…”

“…The randomized nature of the fields would allow for a first survey of Galactic disk and halo substellar objects, down to free-floating super-Jupiters (e.g., Ryan et al 2017;Deacon 2018). These parallel searches for low/sub-stellar objects benefit from color information (Holwerda et al 2018), accurate astrometry, or grism information; but they derive their statistical power from the randomized fields.…”